The challenge of unprecedented floods and droughts in risk management.

Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3.

Nocturnal pulse oximetry for the detection and prediction of acute mountain sickness: An observational study.

Acute mountain sickness (AMS) is a well-studied illness defined by clinical features (e.g., headache and nausea), as assessed by the Lake Louise score (LLS). Although obvious in its severe form, early stages of AMS are poorly defined and easily confused with common travel-related conditions. Measurement of hypoxaemia, the cause of AMS, should be helpful, yet to date its utility for identifying AMS susceptibility remains unclear. This study quantified altitude-induced hypoxaemia in individuals during an ascent to 4800 m to determine the utility of nocturnal pulse oximetry measurements for prediction of AMS. Eighteen individuals (36 ± 16 years of age) ascended to 4800 m over 12 days. Symptomology of AMS was assessed each morning via LLS criteria, with participants categorized as either AMS-positive (LLS ≥ 3 with headache) or AMS-negative. Overnight peripheral oxygen saturations (ov- S p O 2 ${{S}_{{\mathrm{p}}{{{\mathrm{O}}}_2}}}$ ) were recorded continuously (1 Hz) using portable oximeters. Derivatives of these recordings were compared between AMS-positive and -negative subjects (Mann-Whitney U-test). Exploratory analyses (Pearson's) were conducted to investigate relationships between overnight parameters and AMS severity. Overnight derivatives, including ov- S p O 2 ${{S}_{{\mathrm{p}}{{{\mathrm{O}}}_2}}}$ , heart rate/ov- S p O 2 ${{S}_{{\mathrm{p}}{{{\mathrm{O}}}_2}}}$ , variance, oxygen desaturation index, hypoxic burden and total sleep time at <80% S p O 2 ${{S}_{{\mathrm{p}}{{{\mathrm{O}}}_2}}}$ , all differed significantly between AMS-positive and -negative subjects (all P < 0.01), with cumulative/relative frequency plots highlighting these differences visually. Exploratory analysis revealed that ov- S p O 2 ${{S}_{{\mathrm{p}}{{{\mathrm{O}}}_2}}}$ from 3850 m was correlated with peak LLS at 4800 m (r = 0.58-0.61). The findings highlight the potential for overnight oximetry to predict AMS susceptibility during ascent to high altitude. Further investigation is required to develop, evaluate and optimize predictive models to improve AMS management and prevention.

Development of Resorbable Phosphate-Based Glass Microspheres as MRI Contrast Media Agents.

In this research, resorbable phosphate-based glass (PBG) compositions were developed using varying modifier oxides including iron (Fe2O3), copper (CuO), and manganese (MnO2), and then processed via a rapid single-stage flame spheroidisation process to manufacture dense (i.e., solid) and highly porous microspheres. Solid (63-200 µm) and porous (100-200 µm) microspheres were produced and characterised via SEM, XRD, and EDX to investigate their surface topography, structural properties, and elemental distribution. Complementary NMR investigations revealed the formation of Q2, Q1, and Q0 phosphate species within the porous and solid microspheres, and degradation studies performed to evaluate mass loss, particle size, and pH changes over 28 days showed no significant differences among the microspheres (63-71 µm) investigated. The microspheres produced were then investigated using clinical (1.5 T) and preclinical (7 T) MRI systems to determine the R1 and R2 relaxation rates. Among the compositions investigated, manganese-based porous and solid microspheres revealed enhanced levels of R2 (9.7-10.5 s-1 for 1.5 T; 17.1-18.9 s-1 for 7 T) and R1 (3.4-3.9 s-1 for 1.5 T; 2.2-2.3 s-1 for 7 T) when compared to the copper and iron-based microsphere samples. This was suggested to be due to paramagnetic ions present in the Mn-based microspheres. It is also suggested that the porosity in the resorbable PBG porous microspheres could be further explored for loading with drugs or other biologics. This would further advance these materials as MRI theranostic agents and generate new opportunities for MRI contrast-enhancement oral-delivery applications.

Comparing the Accuracy of Peripapillary OCT Scans and Visual Fields to Detect Glaucoma Worsening.

PURPOSE: To compare the accuracy of detecting moderate and rapid rates of glaucoma worsening over a 2-year period with different numbers of OCT scans and visual field (VF) tests in a large sample of glaucoma and glaucoma suspect eyes. DESIGN: Descriptive and simulation study. PARTICIPANTS: The OCT sample comprised 12 150 eyes from 7392 adults with glaucoma or glaucoma suspect status followed up at the Wilmer Eye Institute from 2013 through 2021. The VF sample comprised 20 583 eyes from 10 958 adults from the same database. All eyes had undergone at least 5 measurements over follow-up from the Zeiss Cirrus OCT or Humphrey Field Analyzer. METHODS: Within-eye rates of change in retinal nerve fiber layer (RNFL) thickness and mean deviation (MD) were measured using linear regression. For each measured rate, simulated measurements of RNFL thickness and MD were generated using the distributions of residuals. Simulated rates of change for different numbers of OCT scans and VF tests over a 2-year period were used to estimate the accuracy of detecting moderate (75th percentile) and rapid (90th percentile) worsening for OCT and VF. Accuracy was defined as the percentage of simulated eyes in which the true rate of worsening (the rate without measurement error) was at or less than a criterion rate (e.g., 75th or 90th percentile). MAIN OUTCOME MEASURES: The accuracy of diagnosing moderate and rapid rates of glaucoma worsening for different numbers of OCT scans and VF tests over a 2-year period. RESULTS: Accuracy was less than 50% for both OCT and VF when diagnosing worsening after a 2-year period. OCT accuracy was 5 to 10 percentage points higher than VF accuracy at detecting moderate worsening and 10 to 15 percentage points higher for rapid worsening. Accuracy increased by more than 17 percentage points when using both OCT and VF to detect worsening, that is, when relying on either OCT or VF to be accurate. CONCLUSIONS: More frequent OCT scans and VF tests are needed to improve the accuracy of diagnosing glaucoma worsening. Accuracy greatly increases when relying on both OCT and VF to detect worsening. FINANCIAL DISCLOSURE(S): The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Evidence-Based Guidelines for the Number of Peripapillary OCT Scans Needed to Detect Glaucoma Worsening.

PURPOSE: To estimate the number of OCT scans necessary to detect moderate and rapid rates of retinal nerve fiber layer (RNFL) thickness worsening at different levels of accuracy using a large sample of glaucoma and glaucoma-suspect eyes. DESIGN: Descriptive and simulation study. PARTICIPANTS: Twelve thousand one hundred fifty eyes from 7392 adult patients with glaucoma or glaucoma-suspect status followed up at the Wilmer Eye Institute from 2013 through 2021. All eyes had at least 5 measurements of RNFL thickness on the Cirrus OCT (Carl Zeiss Meditec) with signal strength of 6 or more. METHODS: Rates of RNFL worsening for average RNFL thickness and for the 4 quadrants were measured using linear regression. Simulations were used to estimate the accuracy of detecting worsening-defined as the percentage of patients in whom the true rate of RNFL worsening was at or less than different criterion rates of worsening when the OCT-measured rate was also at or less than these criterion rates-for two different measurement strategies: evenly spaced (equal time intervals between measurements) and clustered (approximately half the measurements at each end point of the period). MAIN OUTCOME MEASURES: The 75th percentile (moderate) and 90th percentile (rapid) rates of RNFL worsening for average RNFL thickness and the accuracy of diagnosing worsening at these moderate and rapid rates. RESULTS: The 75th and 90th percentile rates of worsening for average RNFL thickness were -1.09 µm/year and -2.35 µm/year, respectively. Simulations showed that, for the average measurement frequency in our sample of approximately 3 OCT scans over a 2-year period, moderate and rapid RNFL worsening were diagnosed accurately only 47% and 40% of the time, respectively. Estimates for the number of OCT scans needed to achieve a range of accuracy levels are provided. For example, 60% accuracy requires 7 measurements to detect both moderate and rapid worsening within a 2-year period if the more efficient clustered measurement strategy is used. CONCLUSIONS: To diagnose RNFL worsening more accurately, the number of OCT scans must be increased compared with current clinical practice. A clustered measurement strategy reduces the number of scans required compared with evenly spacing measurements.

Predicting Visual Field Worsening with Longitudinal OCT Data Using a Gated Transformer Network.

PURPOSE: To identify visual field (VF) worsening from longitudinal OCT data using a gated transformer network (GTN) and to examine how GTN performance varies for different definitions of VF worsening and different stages of glaucoma severity at baseline. DESIGN: Retrospective longitudinal cohort study. PARTICIPANTS: A total of 4211 eyes (2666 patients) followed up at the Johns Hopkins Wilmer Eye Institute with at least 5 reliable VF results and 1 reliable OCT scan within 1 year of each reliable VF test. METHODS: For each eye, we used 3 trend-based methods (mean deviation [MD] slope, VF index slope, and pointwise linear regression) and 3 event-based methods (Guided Progression Analysis, Collaborative Initial Glaucoma Treatment Study scoring system, and Advanced Glaucoma Intervention Study [AGIS] scoring system) to define VF worsening. Additionally, we developed a "majority of 6" algorithm (M6) that classifies an eye as worsening if 4 or more of the 6 aforementioned methods classified the eye as worsening. Using these 7 reference standards for VF worsening, we trained 7 GTNs that accept a series of at least 5 as input OCT scans and provide as output a probability of VF worsening. Gated transformer network performance was compared with non-deep learning models with the same serial OCT input from previous studies-linear mixed-effects models (MEMs) and naive Bayes classifiers (NBCs)-using the same training sets and reference standards as for the GTN. MAIN OUTCOME MEASURES: Area under the receiver operating characteristic curve (AUC). RESULTS: The M6 labeled 63 eyes (1.50%) as worsening. The GTN achieved an AUC of 0.97 (95% confidence interval, 0.88-1.00) when trained with M6. Gated transformer networks trained and optimized with the other 6 reference standards showed an AUC ranging from 0.78 (MD slope) to 0.89 (AGIS). The 7 GTNs outperformed all 7 MEMs and all 7 NBCs accordingly. Gated transformer network performance was worse for eyes with more severe glaucoma at baseline. CONCLUSIONS: Gated transformer network models trained with OCT data may be used to identify VF worsening. After further validation, implementing such models in clinical practice may allow us to track functional worsening of glaucoma with less onerous structural testing. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

The haemodynamics of the human placenta in utero.

We have used magnetic resonance imaging (MRI) to provide important new insights into the function of the human placenta in utero. We have measured slow net flow and high net oxygenation in the placenta in vivo, which are consistent with efficient delivery of oxygen from mother to fetus. Our experimental evidence substantiates previous hypotheses on the effects of spiral artery remodelling in utero and also indicates rapid venous drainage from the placenta, which is important because this outflow has been largely neglected in the past. Furthermore, beyond Braxton Hicks contractions, which involve the entire uterus, we have identified a new physiological phenomenon, the 'utero-placental pump', by which the placenta and underlying uterine wall contract independently of the rest of the uterus, expelling maternal blood from the intervillous space.

Effectiveness of Netarsudil versus Brimonidine in Eyes already Being Treated with Glaucoma Medications at a Single Academic Tertiary Care Practice: A Comparative Study.

Background: Rho kinase inhibitors, such as netarsudil, are a relatively new class of medications recently introduced into the market for the treatment of glaucoma, the leading cause of irreversible blindness in the world. Previous clinical trials have studied netarsudil's efficacy when used as a first- or second-line agent but limited studies have investigated its effectiveness in the real world where it is more commonly used as a third, fourth, or fifth agent in combination with other topical medications. Equally important, prior studies have not compared its effectiveness to its peer medications in these settings. Objective: To compare intraocular pressure (IOP) lowering after initiation of netarsudil or brimonidine therapy in patients with glaucoma using >2 medications for IOP management. Methods: A chart review of 369 eyes from 279 patients followed at a single academic tertiary practice was performed with an institutional review board waiver of consent to compare IOP lowering after prescription of netarsudil (n = 176) versus brimonidine (n = 193) as a third, fourth, or fifth IOP-lowering agent. Patients were identified by querying the electronic medical record for those with a glaucoma-related diagnosis who were prescribed either medication. Five sequential IOP measurements were obtained to determine the mean change in IOP before and after treatment (ΔIOP = mean IOP4,5 - mean IOP1,2,3). A multilevel linear mixed-effects model assessed the influence of medication (independent variable) on ΔIOP (dependent variable). Additional independent variables of interest included the number of glaucoma medications at baseline, age, sex, glaucoma type and severity, race, and pretreatment IOP. Bootstrap analysis was performed to remove sampling bias and confirm mixed-effects model findings. Kaplan-Meier survival analysis evaluated the probability of requiring additional intervention within 3 years following the date of medication prescription. Results: The unadjusted mean (SD) ΔIOP for netarsudil and brimonidine was -2.20 (4.11) mm Hg and -2.21 (3.25) mm Hg, respectively (P = 0.484). The adjusted linear mixed-effects models and bootstrap analysis demonstrated that there was no statistical difference in IOP-lowering effectiveness between the medications. Netarsudil and brimonidine failed to adequately control IOP at similar rates with 42% and 47% probabilities of survival respectively by the 3-year follow-up (P = 0.520). Conclusions: When escalating pharmacologic therapy, the IOP-lowering effect of netarsudil appeared to be similar to that produced by brimonidine. (Curr Ther Res Clin Exp. 2023; 84:XXX-XXX).

The Effect of Achieving Target Intraocular Pressure on Visual Field Worsening.

PURPOSE: To estimate the effect of achieving target intraocular pressure (IOP) values on visual field (VF) worsening in a treated clinical population. DESIGN: Retrospective analysis of longitudinal data. PARTICIPANTS: A total of 2852 eyes of 1688 patients with glaucoma-related diagnoses treated in a tertiary care practice. All included eyes had at least 5 reliable VF tests and 5 IOP measures on separate visits along with at least 1 target IOP defined by a clinician on the first or second visit. METHODS: The primary dependent variable was the slope of the mean deviation (MD) over time (decibels [dB]/year). The primary independent variable was mean target difference (measured IOP - target IOP). We created simple linear regression models and mixed-effects linear models to study the relationship between MD slope and mean target difference for individual eyes. In the mixed-effects models, we included an interaction term to account for disease severity (mild/suspect, moderate, or advanced) and a spline term to account for the differing effects of achieving target IOP (target difference ≤0) and failing to achieve target IOP (target difference >0). MAIN OUTCOME MEASURES: Rate of change in MD slope (changes in dB/year) per 1 mmHg change in target difference at different stages of glaucoma severity. RESULTS: Across all eyes, a simple linear regression model demonstrated that a 1 mmHg increase in target difference had a -0.018 dB/year (confidence interval [CI], -0.026 to -0.011; P < 0.05) effect on MD slope. The mixed-effects model shows that eyes with moderate disease that fail to achieve their target IOP experience the largest effects, with a 1 mmHg increase in target difference resulting in a -0.119 dB/year (CI, -0.168 to -0.070; P < 0.05) worse MD slope. The effects of missing target IOP on VF worsening were more pronounced than the effect of absolute level of IOP on VF worsening, where a 1 mmHg increase in IOP had a -0.004 dB/year (CI, -0.011 to 0.003; P > 0.05) effect on the MD slope. CONCLUSIONS: In treated patients, failing to achieve target IOP was associated with more rapid VF worsening. Eyes with moderate glaucoma experienced the greatest VF worsening from failing to achieve target IOP.

The middle cerebral artery blood velocity response to acute normobaric hypoxia occurs independently of changes in ventilation in humans.

NEW FINDINGS: What is the central question of this study? Does the ventilatory response to moderate acute hypoxia increase cerebral perfusion independently of changes in arterial oxygen tension in humans? What is the main finding and its importance? The ventilatory response does not increase middle cerebral artery mean blood velocity during moderate isocapnic acute hypoxia beyond that elicited by reduced oxygen saturation. ABSTRACT: Hypoxia induces ventilatory, cardiovascular and cerebrovascular adjustments to defend against reductions in systemic oxygen delivery. We aimed to determine whether the ventilatory response to moderate acute hypoxia increases cerebral perfusion independently of changes in arterial oxygenation. Eleven young healthy individuals were exposed to four 15 min experimental conditions: (1) normoxia (partial pressure of end-tidal oxygen, PETO2  = 100 mmHg), (2) hypoxia ( PETO2  = 50 mmHg), (3) normoxia with breathing volitionally matched to levels observed during hypoxia (hyperpnoea; PETO2  = 100 mmHg) and (4) hypoxia ( PETO2  = 50 mmHg) with respiratory frequency and tidal volume volitionally matched to levels observed during normoxia (i.e., restricted breathing (RB)). Isocapnia was maintained in all conditions. Middle cerebral artery mean blood velocity (MCA Vmean ), assessed by transcranial Doppler ultrasound, was increased during hypoxia (58 ± 12 cm/s, P = 0.04) and hypoxia + RB (61 ± 14 cm/s, P < 0.001) compared to normoxia (55 ± 11 cm/s), while it was unchanged during hyperpnoea (52 ± 13 cm/s, P = 0.08). MCA Vmean was not different between hypoxia and hypoxia + RB (P > 0.05). These findings suggest that the hypoxic ventilatory response does not increase cerebral perfusion, indexed using MCA Vmean , during moderate isocapnic acute hypoxia beyond that elicited by reduced oxygen saturation.

Novel benzoxazines as inhibitors of angiogenesis.

Dysregulation of angiogenesis has been associated with many pathological disorders, including cancer; where angiogenesis has been found to be critical for the maintenance and metastasis of tumours. One of the pathways involved in the regulation of angiogenesis is the phosphatidylinositol3-kinase (PI3K) signalling pathway. The PI3K family consists of enzymes that phosphorylate the 3-OH of the inositol ring of phosphatidyl inositol. There are four isoforms, PI3Kα, PI3Kß, PI3Kγ and PI3Kδ, that are signalling intermediaries involved in numerous pathways that sustain and maintain the tumours. In this study, we screened eight novel benzoxazine inhibitors of both PI3K isoforms and the related DNA-PK, for their anti-angiogenic effects. Our findings identified the novel benzoxazine (7, 8 (substituted)-2-morpholino-benz (1,3) oxazine: LTUSI122) to be non-toxic at concentrations up to 5 µM, while exhibiting significant inhibition of various aspects of angiogenesis including endothelial proliferation, migration and tube formation. The molecular mechanisms were examined using an angiogenesis array, revealing inhibition of several proliferative and migratory angiogenic factors, including VEGFR, MMP, IL-8, uPAR and MCP; and stimulation of the endogenous inhibitor, endostatin. We hypothesize that these anti-angiogenic effects are mediated by targeting an important signaling intermediary, PI3Kα, and subsequently its action on vascular endothelial growth factor (VEGF, a key growth factor in the process of angiogenesis). If used in combination with more targeted therapies, LTUSI122 could reduce tumour growth and increase the efficacy of these treatments.

Effect of global cardiac ischemia on human ventricular fibrillation: insights from a multi-scale mechanistic model of the human heart.

Acute regional ischemia in the heart can lead to cardiac arrhythmias such as ventricular fibrillation (VF), which in turn compromise cardiac output and result in secondary global cardiac ischemia. The secondary ischemia may influence the underlying arrhythmia mechanism. A recent clinical study documents the effect of global cardiac ischaemia on the mechanisms of VF. During 150 seconds of global ischemia the dominant frequency of activation decreased, while after reperfusion it increased rapidly. At the same time the complexity of epicardial excitation, measured as the number of epicardical phase singularity points, remained approximately constant during ischemia. Here we perform numerical studies based on these clinical data and propose explanations for the observed dynamics of the period and complexity of activation patterns. In particular, we study the effects on ischemia in pseudo-1D and 2D cardiac tissue models as well as in an anatomically accurate model of human heart ventricles. We demonstrate that the fall of dominant frequency in VF during secondary ischemia can be explained by an increase in extracellular potassium, while the increase during reperfusion is consistent with washout of potassium and continued activation of the ATP-dependent potassium channels. We also suggest that memory effects are responsible for the observed complexity dynamics. In addition, we present unpublished clinical results of individual patient recordings and propose a way of estimating extracellular potassium and activation of ATP-dependent potassium channels from these measurements.

Retina-V1 model of detectability across the visual field.

A practical model is proposed for predicting the detectability of targets at arbitrary locations in the visual field, in arbitrary gray scale backgrounds, and under photopic viewing conditions. The major factors incorporated into the model include (a) the optical point spread function of the eye, (b) local luminance gain control (Weber's law), (c) the sampling array of retinal ganglion cells, (d) orientation and spatial frequency-dependent contrast masking, (e) broadband contrast masking, and (f) efficient response pooling. The model is tested against previously reported threshold measurements on uniform backgrounds (the ModelFest data set and data from Foley, Varadharajan, Koh, & Farias, 2007) and against new measurements reported here for several ModelFest targets presented on uniform, 1/f noise, and natural backgrounds at retinal eccentricities ranging from 0° to 10°. Although the model has few free parameters, it is able to account quite well for all the threshold measurements.

The Impact of Social Vulnerability on Structural and Functional Glaucoma Severity, Worsening, and Variability.

PURPOSE: To determine the associations between social vulnerability index (SVI) and baseline severity, worsening, and variability of glaucoma, as assessed by visual field (VF) and OCT. DESIGN: Retrospective longitudinal cohort study. PARTICIPANTS: Adults with glaucoma or glaucoma suspect status in 1 or both eyes. Visual fields were derived from 7897 eyes from 4482 patients, while OCTs were derived from 6271 eyes from 3976 patients. All eyes had a minimum of 5 tests over follow-up using either the Humphrey Field Analyzer or the Cirrus HD-OCT. METHODS: Social vulnerability index, which measures neighborhood-level environmental factors, was linked to patients' addresses at the census tract level. Rates of change in mean deviation (MD) and retinal nerve fiber layer (RNFL) thickness were computed using linear regression. The slope of the regression line was used to assess worsening, while the standard deviation of residuals was used as a measure of variability. Multivariable linear mixed-effects models were used to investigate the impact of SVI on baseline, worsening, and variability in both MD and RNFL. We further explored the interaction effect of mean intraocular pressure (IOP) and SVI on worsening in MD and RNFL. MAIN OUTCOME MEASURES: Glaucoma severity defined based on baseline MD and RNFL thickness. Worsening defined as MD and RNFL slope. Variability defined as the standard deviation of the residuals obtained from MD and RNFL slopes. RESULTS: Increased (worse) SVI was significantly associated with worse baseline MD (ß = -1.07 dB, 95% confidence interval [CI]: [-1.54, -0.60]), thicker baseline RNFL (ß = 2.46 µm, 95% CI: [0.75, 4.17]), greater rates of RNFL loss (ß = -0.12 µm, 95% CI: [-0.23, -0.02]), and greater VF variability (ß = 0.16 dB, 95% CI: [0.07, 0.24]). Having worse SVI was associated with worse RNFL loss with increases in IOP (ßinteraction = -0.07, 95% CI: [-0.12, -0.02]). CONCLUSIONS: Increased SVI score is associated with worse functional (VF) loss at baseline, higher rates of structural (OCT) worsening over time, higher VF variability, and a greater effect of IOP on RNFL loss. Further studies are needed to enhance our understanding of these relationships and establish their cause. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Development and validation of a questionnaire for assessing visual and auditory spatial localization abilities in dual sensory impairment.

Spatial localization is important for social interaction and safe mobility, and relies heavily on vision and hearing. While people with vision or hearing impairment compensate with their intact sense, people with dual sensory impairment (DSI) may require rehabilitation strategies that take both impairments into account. There is currently no tool for assessing the joint effect of vision and hearing impairment on spatial localization in this large and increasing population. To this end, we developed a novel Dual Sensory Spatial Localization Questionnaire (DS-SLQ) that consists of 35 everyday spatial localization tasks. The DS-SLQ asks participants about their difficulty completing different tasks using only vision or hearing, as well as the primary sense they rely on for each task. We administered the DS-SLQ to 104 participants with heterogenous vision and hearing status. Rasch analysis confirmed the psychometric validity of the DS-SLQ and the feasibility of comparing vision and hearing spatial abilities in a unified framework. Vision and hearing impairment were associated with decreased visual and auditory spatial abilities. Differences between vision and hearing abilities predicted overall sensory reliance patterns. In DSI rehabilitation, DS-SLQ may be useful for measuring vision and hearing spatial localization abilities and predicting the better sense for completing different spatial localization tasks.

Detecting Glaucoma Worsening Using Optical Coherence Tomography Derived Visual Field Estimates.

Objective: Multiple studies have attempted to generate visual field (VF) mean deviation (MD) estimates using cross-sectional optical coherence tomography (OCT) data. However, whether such models offer any value in detecting longitudinal VF progression is unclear. We address this by developing a machine learning (ML) model to convert OCT data to MD and assessing its ability to detect longitudinal worsening. Design: Retrospective, longitudinal study. Participants: A model dataset of 70,575 paired OCT/VFs to train an ML model converting OCT to VF-MD. A separate progression dataset of 4,044 eyes with ≥ 5 paired OCT/VFs to assess the ability of OCT-derived MD to detect worsening. Progression dataset eyes had two additional unpaired VFs (≥ 7 total) to establish a "ground truth" rate of progression defined by MD slope. Methods: We trained an ML model using paired VF/OCT data to estimate MD measurements for each OCT scan (OCT-MD). We used this ML model to generate longitudinal OCT-MD estimates for progression dataset eyes. We calculated MD slopes after substituting/supplementing VF-MD with OCT-MD and measured the ability to detect progression. We labeled true progressors using a ground truth MD slope <0.5 dB/year calculated from ≥ 7 VF-MD measurements. We compared the area under the curve (AUC) of MD slopes calculated using both VF-MD (with <7 measurements) and OCT-MD. Because we found OCT-MD substitution had a statistically inferior AUC to VF-MD, we simulated the effect of reducing OCT-MD mean absolute error (MAE) on the ability to detect worsening. Main Outcome Measures: AUC. Results: OCT-MD estimates had an MAE of 1.62 dB. AUC of MD slopes with partial OCT-MD substitution was significantly worse than the VF-MD slope. Supplementing VF-MD with OCT-MD also did not improve AUC, regardless of MAE. OCT-MD estimates needed an MAE ≤ 1.00 dB before AUC was statistically similar to VF-MD alone. Conclusion: ML models converting OCT data to VF-MD with error levels lower than published in prior work (MAE: 1.62 dB) were inferior to VF-MD data for detecting trend-based VF progression. Models converting OCT data to VF-MD must achieve better prediction errors (MAE ≤ 1 dB) to be clinically valuable at detecting VF worsening.

Deep learning-based identification of eyes at risk for glaucoma surgery.

To develop and evaluate the performance of a deep learning model (DLM) that predicts eyes at high risk of surgical intervention for uncontrolled glaucoma based on multimodal data from an initial ophthalmology visit. Longitudinal, observational, retrospective study. 4898 unique eyes from 4038 adult glaucoma or glaucoma-suspect patients who underwent surgery for uncontrolled glaucoma (trabeculectomy, tube shunt, xen, or diode surgery) between 2013 and 2021, or did not undergo glaucoma surgery but had 3 or more ophthalmology visits. We constructed a DLM to predict the occurrence of glaucoma surgery within various time horizons from a baseline visit. Model inputs included spatially oriented visual field (VF) and optical coherence tomography (OCT) data as well as clinical and demographic features. Separate DLMs with the same architecture were trained to predict the occurrence of surgery within 3 months, within 3-6 months, within 6 months-1 year, within 1-2 years, within 2-3 years, within 3-4 years, and within 4-5 years from the baseline visit. Included eyes were randomly split into 60%, 20%, and 20% for training, validation, and testing. DLM performance was measured using area under the receiver operating characteristic curve (AUC) and precision-recall curve (PRC). Shapley additive explanations (SHAP) were utilized to assess the importance of different features. Model prediction of surgery for uncontrolled glaucoma within 3 months had the best AUC of 0.92 (95% CI 0.88, 0.96). DLMs achieved clinically useful AUC values (> 0.8) for all models that predicted the occurrence of surgery within 3 years. According to SHAP analysis, all 7 models placed intraocular pressure (IOP) within the five most important features in predicting the occurrence of glaucoma surgery. Mean deviation (MD) and average retinal nerve fiber layer (RNFL) thickness were listed among the top 5 most important features by 6 of the 7 models. DLMs can successfully identify eyes requiring surgery for uncontrolled glaucoma within specific time horizons. Predictive performance decreases as the time horizon for forecasting surgery increases. Implementing prediction models in a clinical setting may help identify patients that should be referred to a glaucoma specialist for surgical evaluation.

Assessment of linear regression of peripapillary optical coherence tomography retinal nerve fiber layer measurements to forecast glacuoma trajectory.

Linear regression of optical coherence tomography measurements of peripapillary retinal nerve fiber layer thickness is often used to detect glaucoma progression and forecast future disease course. However, current measurement frequencies suggest that clinicians often apply linear regression to a relatively small number of measurements (e.g., less than a handful). In this study, we estimate the accuracy of linear regression in predicting the next reliable measurement of average retinal nerve fiber layer thickness using Zeiss Cirrus optical coherence tomography measurements of average retinal nerve fiber layer thickness from a sample of 6,471 eyes with glaucoma or glaucoma-suspect status. Linear regression is compared to two null models: no glaucoma worsening, and worsening due to aging. Linear regression on the first M ≥ 2 measurements was significantly worse at predicting a reliable M+1st measurement for 2 ≤ M ≤ 6. This range was reduced to 2 ≤ M ≤ 5 when retinal nerve fiber layer thickness measurements were first "corrected" for scan quality. Simulations based on measurement frequencies in our sample-on average 393 ± 190 days between consecutive measurements-show that linear regression outperforms both null models when M ≥ 5 and the goal is to forecast moderate (75th percentile) worsening, and when M ≥ 3 for rapid (90th percentile) worsening. If linear regression is used to assess disease trajectory with a small number of measurements over short time periods (e.g., 1-2 years), as is often the case in clinical practice, the number of optical coherence tomography examinations needs to be increased.

Validation of a Wearable Virtual Reality Perimeter for Glaucoma Staging, The NOVA Trial: Novel Virtual Reality Field Assessment.

Purpose: Compare estimated sensitivities of SITA-Standard to the RATA-Standard algorithm of the Radius virtual reality perimeter (VRP), and measure concordance in glaucoma staging. Methods: One hundred adult glaucoma patients-half with suspect or mild glaucoma, and half with moderate or severe-from five clinics performed four 24-2 visual field tests during a single visit, two with the Humphrey Field Analyzer (HFA) and two with Radius, in randomized order: HRHR or RHRH. Only one eye was tested per participant. We used the Wilcoxon rank sum test with Bonferroni correction to compare distributions of estimated sensitivities across all 54 test locations over the 15 to 40 dB measurement range of the Radius. Weighted kappa measured concordance in glaucoma staging between two masked glaucoma experts using Medicare definitions of severity. Results: A total of 62 OD and 38 OS eyes were tested. Estimated sensitivities for SITA-Standard and RATA-Standard were not significantly different for OD, but were for OS-likely because of SITA-Standard OD and OS being significantly different in our sample, but not for RATA-Standard. Low agreement was observed between 15 to 22 dB. Concordance in glaucoma staging was high for both graders: kappa = 0.91 and kappa = 0.93. Average test duration was 298 seconds for RATA-Standard and 341 seconds for SITA-Standard. The correlation in mean deviation was 0.94. Conclusions: Estimated sensitivities of RATA-Standard are comparable to SITA-Standard between 23 to 40 dB with high concordance in glaucoma staging. Translational Relevance: Radius VRP is statistically noninferior to HFA when staging glaucoma using Medicare definitions.

Opportunities for Improving Glaucoma Clinical Trials via Deep Learning-Based Identification of Patients with Low Visual Field Variability.

PURPOSE: Develop and evaluate the performance of a deep learning model (DLM) that forecasts eyes with low future visual field (VF) variability, and study the impact of using this DLM on sample size requirements for neuroprotective trials. DESIGN: Retrospective cohort and simulation study. METHODS: We included 1 eye per patient with baseline reliable VFs, OCT, clinical measures (demographics, intraocular pressure, and visual acuity), and 5 subsequent reliable VFs to forecast VF variability using DLMs and perform sample size estimates. We estimated sample size for 3 groups of eyes: all eyes (AE), low variability eyes (LVE: the subset of AE with a standard deviation of mean deviation [MD] slope residuals in the bottom 25th percentile), and DLM-predicted low variability eyes (DLPE: the subset of AE predicted to be low variability by the DLM). Deep learning models using only baseline VF/OCT/clinical data as input (DLM1), or also using a second VF (DLM2) were constructed to predict low VF variability (DLPE1 and DLPE2, respectively). Data were split 60/10/30 into train/val/test. Clinical trial simulations were performed only on the test set. We estimated the sample size necessary to detect treatment effects of 20% to 50% in MD slope with 80% power. Power was defined as the percentage of simulated clinical trials where the MD slope was significantly worse from the control. Clinical trials were simulated with visits every 3 months with a total of 10 visits. RESULTS: A total of 2817 eyes were included in the analysis. Deep learning models 1 and 2 achieved an area under the receiver operating characteristic curve of 0.73 (95% confidence interval [CI]: 0.68, 0.76) and 0.82 (95% CI: 0.78, 0.85) in forecasting low VF variability. When compared with including AE, using DLPE1 and DLPE2 reduced sample size to achieve 80% power by 30% and 38% for 30% treatment effect, and 31% and 38% for 50% treatment effect. CONCLUSIONS: Deep learning models can forecast eyes with low VF variability using data from a single baseline clinical visit. This can reduce sample size requirements, and potentially reduce the burden of future glaucoma clinical trials. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.